BACKGROUND

Mobile health (mHealth) provides health information through electronic devices, even at home. The escalating prevalence of sedentary behaviors among older adults, which leads to increased adverse health outcomes, underscores the pressing need for a comprehensive understanding of the effectiveness of mHealth interventions.

OBJECTIVE

This study aims to examine the effectiveness of mHealth interventions in the sitting time of older adults (age 55 years).

METHODS

A systematic review and meta-analysis of randomized controlled trials was conducted to evaluate the effects of mHealth interventions on total sitting time during waking hours, excluding sleep. A literature search was conducted using multiple databases, including PubMed, Embase, Web of Science, and Cochrane, covering articles published from the inception of each database through October 2023. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were explicitly applied to structure this report. Methodological quality was assessed using the Cochrane Risk of Bias (ROB 2) tool for randomized controlled trials and the Methodological Index for Non-Randomized Studies (MINORS) tool for nonrandomized studies. Two independent reviewers screened the studies, extracted data, and assessed methodological quality using established criteria. Meta-analyses were performed using Review Manager (version 5.4; Cochrane Collaboration).

RESULTS

Ten studies were identified, of which 3 were included in the meta-analysis, while the remaining 7 were assessed exclusively in the systematic review. The interventions predominantly took place in community settings (n=3) and home-based settings (n=3). Three studies aimed to decrease sedentary behavior and 7 aimed to increase physical activity. The interventions were primarily conducted once daily (n=7) via mobile devices such as smartphones (n=7) and typically involved a single intervention delivered at different time intervals, such as every 15, 20, or 30 minutes (n=4). The interventions typically lasted 12 weeks (n=4) and used objective assessment tools, such as the ActiGraph GT3X+ (n=8). The included studies applied the habit formation theory (n=1), the self-efficacy theory (n=1), the social cognitive theory (n=1), and the social-ecological theory (n=1) as frameworks. Additionally, behavior change techniques, including "goal setting," "problem-solving," "action planning," and "review behavior goal(s)" (n=6), were used. Meta-analysis of the 3 studies included showed a significant decrease in sedentary behavior with mHealth interventions compared with conventional or no interventions (weighted mean difference [WMD]=59.1 min/d, 95% CI 99.1 to 20.2; P=.003).

CONCLUSIONS

mHealth interventions effectively reduce sitting time in older adults. Strategies using interventions with specific frequencies and durations, dedicated mobile monitoring devices, and behavior change techniques showed the potential to reduce sedentary behavior among older adults. These results also underscore the potential of mHealth as a key tool for promoting the well-being of older adults through technology-driven public health efforts.

TRIAL REGISTRATION

PROSPERO CRD42023443926; https://www.crd.york.ac.uk/PROSPERO/view/CRD42023443926.